Age%related!microstructural!differences!quantified!using!myelin!
water!imaging!and!advanced!diffusion!MRI!
! !
Billiet,' T
a,b,c,d,! Vandenbulcke,! M
d,e,! Mädler,! B
f,g,! Peeters,! R
b,d,!
Dhollander,! T
c,h,! Zhang,! H
i,! Deprez,! S
a,b,c,d,! Van! den! Bergh! BRH
j,k,!
Sunaert!S
a,b,c,d,!L!Emsell
a,b,c,d,e!
!
a. Translational! MRI,! Department! of! Imaging! &! Pathology,! KU! Leuven,! Herestraat!49,!Leuven!3000,!Belgium.!
b. Department! of! Radiology,! University! Hospitals! Leuven,! Herestraat! 49,! Leuven!3000,!Belgium!
c. Medical! Imaging! Research! Center! (MIRC),! Herestraat! 49,! Leuven! 3000,! Belgium!!
d. Leuven!Research!Institute!for!Neuroscience!&!Disease!(LIND),!Herestraat! 49,!Leuven!3000,!Belgium!
e. Department! of! Old! Age! Psychiatry,! KU! Leuven,! Herestraat! 49,! Leuven! 3000,!Belgium!
f. Philips!Healthcare,!Philips!Road!14,!Hamburg!20099,!Germany!
g. Department! of! Neurosurgery,! Medical! Centre,! University! of! Bonn,! Sigmund%Freud%Straße!25,!Bonn!53105,!Germany!
h. The! Florey! Institute! of! Neuroscience! and! Mental! Health,! Melbourne,! Victoria,!Australia!
i. !Department!of!Computer!Science!&!Centre!for!Medical!Image!Computing,! University!College!London,!Gower!Street,!London!WC1E!6BT,!UK!
j. Department! of! Psychology,! Tilburg! University,! Tilburg! 5000! LE,! Netherlands!
k. Research! group! on! Health! Psychology,! KU! Leuven,! Tiensestraat! 102,! Leuven!3000,!Belgium!
!
'
'
Corresponding'Author'
! First!Name! Thibo! Last!Name! Billiet! Highest!academic!degree! Master! Professional!title! Ir.! Affiliation! • KU!Leuven!(Imaging!&!Pathology!dpt.!%! Translational! MRI! unit),! Leuven,! Belgium!• University! Hospitals! Leuven! (Radiology),!Leuven,!Belgium!
• Medical!Imaging!Research!Center! • Leuven! research! Institute! of! for!
Neuroscience!&!Disease! Name!and!address!for!correspondence! Thibo!Billiet! Radiology,!University!Hospitals!Leuven! Herestraat!49!%!box!7003! B!–!3000!Leuven! Belgium! Location!of!affiliation! Leuven,!Belgium! Telephone!number! +32!16!34!90!69! Fax!number! +32!16!34!37!65! e%mail!address! [email protected]! !
Abstract'
!
Introduction:!Age%related!microstructural!differences!have!been!detected!using! diffusion!tensor!imaging!(DTI).!Whilst!DTI!is!sensitive!to!the!effects!of!aging,!it!is! not! specific! to! any! underlying! biological! mechanism,! including! demyelination.! Combining! multi%exponential! T2! relaxation! (MET2)! and! multi%shell! diffusion! MRI!(dMRI)!techniques!may!elucidate!such!processes.!
Methods:! Multi%shell! dMRI! and! MET2! data! were! acquired! on! 59! healthy! participants! aged! 17%70! years.! Whole! brain! and! regional! age%associated! correlations! of! measures! related! to! multiple! dMRI! models! (DTI,! diffusion! kurtosis! imaging! (DKI),! neurite! orientation! dispersion! and! density! imaging! (NODDI))!and!myelin!sensitive!MET2!metrics!were!assessed.!
Results:! DTI! and! NODDI! revealed! widespread! increases! in! isotropic! diffusivity! with!increasing!age.!In!frontal!white!matter,!fractional!anisotropy!(FA)!linearly! decreased! with! age,! paralleled! by! increased! ‘neurite’! dispersion! and! no! difference! in! myelin! water! fraction! (MWF).! DKI! measures! and! neurite! density! correlated!well!with!MWF!and!intra%!and!extracellular!water!fraction!(IEWF).! Conclusion:! DTI! estimates! remain! among! the! most! sensitive! markers! for! age% related! alterations! in! white! matter.! NODDI,! DKI! and! MET2! indicate! that! the! initial!decrease!in!frontal!FA!may!be!due!to!increased!axonal!dispersion!rather! than!demyelination.!!
! !
1.'Introduction:' !
Throughout! adulthood,! the! human! brain! undergoes! significant! biophysical! changes! in! both! white! and! grey! matter! (Pannese,! 2011).! In! contrast! to! non% human! primates,! these! maturating! and! regressive! processes! occur! heterochronically!in!different!brain!regions!(Haroutunian,!et!al.,!2014).!!
!
Structural! magnetic! resonance! imaging! (sMRI)! has! played! a! pivotal! role! in! the! context! of! monitoring! and! understanding! the! healthy! ageing! process,! for! example,!by!measuring!atrophy!and!detecting!white!matter!(WM)!lesions!(Fjell,! et!al.,!2009,Raz,!et!al.,!1997,Salat,!et!al.,!2009).!However,!single!contrast!sMRI!is! suboptimal!for!measuring!microstructural!changes,!including!myelination,!which! may!predate!atrophy!(Haroutunian,!et!al.,!2014).! ! Other!MRI!based!techniques,!such!as!those!that!are!sensitive!to!the!direction!of! water! diffusion! (diffusion! MRI)! or! myelin! content! (relaxometry,! magnetization! transfer! imaging)! are! increasingly! being! applied! to! study! lifespan! effects.! The! most!widely!used!of!these!approaches!is!diffusion!tensor!imaging!(DTI)!(Basser,! et! al.,! 1994).! Fractional! anisotropy! (FA)! describes! the! degree! of! non%isotropic! diffusion! and! is! a! popular,! non%specific! DTI! metric! that! is! used! as! a! general! indicator! of! microstructural! status! because! of! its! sensitivity! to! changes! in! cell! density,! size,! number! and! myelin! status! (Beaulieu,! 2002,Beaulieu! and! Allen,! 1994).! See! (Tournier,! et! al.,! 2011)! for! a! review.! Age%related! differences! in! FA,! mean! diffusivity! (MD),! and! radial! diffusivity! (RD)! have! been! found! in! various! WM! regions.! The! changes! are! often! non%linear! (quadratic)! with! an! initial! increase! in! FA! and! decrease! in! MD! and! RD! followed! by! a! reversal! that! is! frequently! attributed! to! deficits! in! axonal! membrane! (myelin)! integrity.! The! greatest!changes!are!often!found!in!the!anterior!corpus!callosum!(Bartzokis,!et! al.,!2012,Brickman,!et!al.,!2012,Davis,!et!al.,!2009,Inano,!et!al.,!2011,Lebel,!et!al.,! 2012,Pfefferbaum,!et!al.,!2000,Salat,!et!al.,!2005,Sullivan!and!Pfefferbaum,!2006).!! ! Whilst!DTI!is!a!popular!technique,!it!is!not!without!significant!limitations,! many!of!which!relate!to!the!simplicity!of!the!tensor!model!(Jones!and!Cercignani,!
2010).!In!response,!novel!non%tensor!based!diffusion!MRI!techniques!have!been! developed.! In! contrast! to! DTI,! Diffusion! Kurtosis! Imaging! (DKI)! also! measures! non%Gaussian! diffusion! and! may! provide! additional! and! complementary! information!to!DTI!(Jensen!and!Helpern,!2010,Jensen,!et!al.,!2005).!To!date,!only! a!few!studies!have!applied!this!technique!to!study!differences!across!the!lifespan.! In!these!studies,!mean!kurtosis!(MK),!a!measure!of!tissue!complexity!was!found! to!increase!in!WM!during!maturation!and!decrease!in!healthy!aging!(Coutu,!et!al.,! 2014,Falangola,!et!al.,!2008,Gong,!et!al.,!2014,Latt,!et!al.,!2013).!! !
Another! advanced! diffusion! MRI! analysis! technique,! neurite! orientation! dispersion!and!density!imaging!(NODDI)(Zhang,!et!al.,!2012)!aims!to!quantify!the! density!and!dispersion!of!neurites!(i.e.!axons!and!dendrites).!These!can!be!seen! as! independent! factors! influencing! anisotropy! and! provide! a! more! biologically! intuitive! model! of! diffusion! changes.! NODDI! has! been! successfully! applied! in! previous!studies!investigating!pathological!changes!(Billiet,!et!al.,!2014a,Lally,!et! al.,! 2014,Winston,! et! al.,! 2014)! and! neonates! (Jelescu,! et! al.,! 2015,Kunz,! et! al.,! 2014,Melbourne,!et!al.,!2013),!but!has!not!yet!been!used!prospectively!in!healthy! ageing.!
!
Diffusion!estimates!have!proven!to!be!sensitive!to!many!microstructural! alterations,! yet! lack! specificity.! Furthermore,! diffusion! MRI! cannot! directly! assess! myelin,! which! has! an! important! role! in! ageing! processes.! ! Several! alternative!MRI!based!techniques!provide!myelin!markers,!including!the!myelin! water!fraction!(MWF)!obtained!from!multi%exponential!T2!relaxation!(MET2,!or! “myelin! water! imaging,! MWI”),! and! magnetization! transfer! imaging! (MTI).! Studies! using! MTI! have! found! evidence! of! potential! age! associated! demyelination;! yet! the! lack! of! specificity! of! these! measures! for! myelin! means! that!MTI!based!findings!need!confirmation!using!alternative!techniques.!In!this! context,! the! MWF! has! superior! specificity! for! myelin! content! (Stanisz,! et! al.,! 2004,Vavasour,! et! al.,! 2011).! A! few! studies! have! been! conducted! assessing! the! evolution!of!myelination!in!neonates!and!children!(Deoni,!et!al.,!2012,Melbourne,! et! al.,! 2013,Whitaker,! et! al.,! 2008)! yet! limited! information! exists! about! the! evolution!of!MET2!metrics!during!adulthood!(Flynn,!et!al.,!2003).!!
!
There! are! undisputable,! heterogeneous! WM! microstructural! changes! associated! with! ageing! as! assessed! using! different! MRI! techniques.! However,! attributing! differences! in! univariate! MRI! measures! to! specific! microstructural! features!is!confounded!by!a!lack!of!specificity!and,!in!the!case!of!novel!measures,! a! lack! of! studies! characterising! their! behaviour! in! healthy! tissue.! In! this! multimodal!MRI!study!we!therefore!aimed!to!quantify!whole!brain!and!regional! age%related!differences!in!both!established!(DTI)!and!novel!diffusion!MRI!metrics! (DKI,!NODDI)!as!well!as!in!the!myelin!specific!MET2!technique!in!a!prospective! sample!of!healthy!individuals.!We!contribute!valuable!normative!data!for!future! studies! using! these! techniques! and! demonstrate! the! added! value! of! using! multiparametric! MRI! data! for! assessing! age%related! WM! microstructural! changes.! ' 2.'Materials'&'Methods'' ! 2.1'Participants' ! Age!and!gender!matched!healthy!volunteers!between!the!ages!of!17!and! 70! years! old! were! recruited! through! local! advertisement! in! the! Leuven! University! Hospital.! Inclusion! criteria! were! the! absence! of! current! medical! illness,! diagnosis! of! a! neurological! or! psychiatric! disorder,! previous! brain! surgery,! traumatic! brain! injury,! use! of! psychotropic! medication,! and! contraindications!to!MRI!scanning.!The!study!was!approved!by!the!local!Ethical! Committee! and! conducted! in! accordance! with! the! Declaration! of! Helsinki.! Originally! sixty%two! volunteers! participated! of! which! fifty%nine! were! retained! (min!age:!17,!max!age!70).!One!dataset!was!discarded!because!of!extensive!white! matter! hyperintensities.! The! remaining! participants! were! free! of! visible! hyperintensities.! Two! datasets! were! discarded! because! of! incomplete! data! acquisition.! Participants! were! randomly! scanned! within! a! timeframe! of! 7! months,! with! the! timing! of! data! acquisition! distributed! evenly! across! the! age% range!studied.!There!were!slightly!more!female!participants!than!males!(f/m!=! 36/23)! but! their! mean! age! did! not! differ! (t! =! 0.49,! p! =! 0.62).! There! was! no!
significant!difference!in!educational!level!across!the!age%range!investigated!(F=! 1.68,!p!=!0.17).!Education!level!in!this!instance!refers!to!the!highest!educational! qualification!(i.e.!most!years!of!education)!obtained!in!Belgium!based!on!5!levels,! which! include:! primary! school,! secondary! school! (i.e.! high! school),! higher! education! of! short! duration! (equivalent! to! professional! bachelor),! higher! education! of! long! duration! (equivalent! to! professional! master)! and! university! degree!(academic!bachelor!+!master).! ! 2.2'Data'acquisition' ! MRI!brain!scans!were!acquired!using!a!3T!MR!scanner!(Achieva;!Philips,! Best,!the!Netherlands)!and!a!32%channel!phased%array!head!coil.! ! 2.2.1!Multi*exponential!T2*relaxation! ! A!3D!GraSE!sequence!was!used!to!acquire!multi%slice!multi%echo!data!of! the!cerebrum!in!under!12!minutes!(Maedler!and!MacKay,!2007,Prasloski,!et!al.,! 2012).! The! data! consisted! of! 32! mid%axial! slices! for! which! 32! echoes! were! acquired!with! TE!=!10!ms!(TE!=!10,!20,!…,!320!ms),!TR!=!1000!ms,!EPI%read!out! factor!of!3!and!voxel!size!1!x!1!x!2.5!mm3.!
!
2.2.2!Diffusion!MRI! !
An! echo%planar! imaging! (EPI),! multi%shell,! high! angular! resolution! diffusion! imaging! (HARDI)! scheme! was! used! consisting! of! diffusion%weighted! images! for! b%values! of! 700,! 1000,! and! 2800! s/mm2,! respectively! applied! along!
25,!40!and!75!uniformly!distributed!directions!(Poot,!et!al.,!2010).!!!Each!series!of! diffusion%weighted!images!was!preceded!by!a!b!=!0!image.!An!additional!7!non% diffusion! weighted! images! were! acquired! yielding! 10! b! =! 0! images! in! total.! Constant!scan!parameters!were!TR/TE!=!7800!ms/90ms,!50!slices,!voxel!size!2.5! x!2.5!x!2.5!mm3,!parallel!imaging!factor!2.!
A! T1%weighted! image! was! acquired! for! anatomical! reference! and! image! registration! purposes! using! a! whole! brain! 3D%TFE! sequence! consisting! of! 182!
contiguous!coronal!slices!with!TE!=!4.6!ms,!TR!=!9.6!ms,!voxel!size!0.98!x!0.98!x! 1.2!mm3.!The!total!scan!time!of!the!protocol!was!approximately!45!minutes.!
!
2.3'Data'preCprocessing' !
The! main! steps! in! the! image%processing! pipeline! are! visualized! in! Figure! 1.! Following! data! quality! assurance! and! correction,! the! MET2! and! diffusion! parameter! maps! were! calculated! in! each! subject! in! native! space.! These! parameter!maps!were!then!brought!into!a!common!template!space!via!a!series!of! controlled!affine!and!non%affine!registration!steps.!The!datasets!were!masked!to! define! which! voxels! should! be! included! as! WM! (based! on! the! T1%weighted! anatomical! image),! and! which! should! be! excluded! e.g! CSF! (including! lateral! ventricles),!subcortical!GM!(including!basal!ganglia!and!thalamus)!and!the!voxels! closest! to! the! cortical! boundary.! Parameter! values! were! then! assessed! in! each! individual!subject!in!masked!template!space.!Each!of!these!steps!is!described!in! more!technical!detail!below.! ! 2.3.1!Quality!assurance!&!calculation!of!quantitative!maps! ! !Multi*exponential!T2!relaxation! The!T2!weighted!volumes!were!visually!checked!for!motion!artifacts!and! in!case!of!a!blurred!first!echo!image,!the!dataset!was!discarded.!! A!decay!curve!was!obtained!in!each!voxel!from!all!T2!weighted!images,!and!was! transformed!into!a!distribution!of!120!mono%exponential!T2!decay!curves!using! regularized!non%negative!least!squares!estimation!(Whittall!and!Mackay,!1989).! We!used!the!extended!phase!graph!algorithm!to!account!for!possible!stimulated! echoes!due!to!non%ideal!refocusing!pulse!flip!angles!(Hennig,!1988,Prasloski,!et! al.,!2011).!!A!1.02!regularization!factor!was!used!during!the!fitting!procedure!to! assure! smooth! T2! amplitude! distributions.! From! the! T2! distributions! the! following! MET2! metrics! were! derived! on! a! voxelwise! basis:! myelin! water! fraction! (MWF)! was! calculated! as! the! area! fraction! between! 10! and! 40! ms! relative! to! total! T2! distribution! area;! intra%! and! extracellular! water! fraction! (IEWF)! as! relative! area! between! 40! and! 200! ms;! IEW%gmT2! is! the! geometric!
mean!T2!time!of!intra%and!extracellular!water;!G%gmT2!is!the!geometric!mean!T2! time!of!the!overall!distribution.!Example!MET2!parameter!maps!are!illustrated!in! Figure!2!and!summarized!in!Table!1B.! ! Diffusion!MRI! All!DWIs!were!visually!investigated!by!looping!through!each!dataset!in!all! three! orthogonal! views.! Datasets! with! clear! artifacts! such! as! signal! dropout,! gross!geometric!distortion!or!bulk!motion!were!discarded.!Satisfactory!datasets! were! corrected! for! eddy%current! and! motion%induced! geometric! distortions! using! the! ExploreDTI! toolbox,! which! is! based! on! the! approach! described! by! Irfanoglu! et! al! (Irfanoglu,! et! al.,! 2012).! This! step! also! included! the! appropriate! reorientation!of!the!B%matrix.!(Leemans,!2009,Leemans!and!Jones,!2009).!From! the! corrected! and! combined! DWIs,! diffusion! tensors! and! diffusion! kurtosis! tensors! were! obtained! per! voxel(Jensen,! et! al.,! 2005),! and! the! following! parameters! were! derived:! axial! diffusivity! (AD),! radial! diffusivity! (RD),! mean! diffusivity! (MD),! fractional! anisotropy! (FA),! axial! kurtosis! (AK),! radial! kurtosis! (RK),! mean! kurtosis! (MK)! and! kurtosis! anisotropy! (KA).! NODDI! metrics! were! derived! using! the! NODDI! toolbox1:! neurite! density! index! (NDI),! orientation!
dispersion!index!(ODI)!and!(Gaussian)!isotropic!fraction!(FISO).!Example!dMRI! parameter!maps!are!illustrated!in!Figure!2!and!summarized!in!Table!1.!
!
2.3.2!Image!registration! !
The! registration! pipeline! is! illustrated! in! Figure! 1.! A! population%based! template! was! constructed! based! on! the! b=2800! shell! of! the! diffusion! MRI! dataset,! using! an! affine! and! subsequently! non%rigid! DTI%based! registration! algorithm! incorporating! tensor! reorientation! (Leemans! and! Jones,! 2009,Van! Hecke,!et!al.,!2007).!The!b!=!2800!shell!was!chosen!for!optimal!angular!contrast.! All!parameter!maps!were!computed!in!native!space!and!then!coregistered!to!this! population%based! template! using! the! following! steps.! First,! the! “Advanced! Normalisation!Tools”!(ANTS)!toolbox!(Avants,!et!al.,!2008)!was!used!to!affinely! register! the! MET2! metrics! to! the! native! T1! image! by! maximization! of! mutual! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
information! between! the! first! echo! image! and! the! T1! image.! Affine! transformations! were! justified! by! the! absence! of! any! geometric! distortions! in! MET2! data.! Next,! the! MET2! metrics! and! T1%based! tissue! classes! were! diffeomorphically!registered!(Avants,!et!al.,!2008)!to!b!=!1000!data!(for!optimal! GM! and! WM! tissue! contrast).! To! optimally! account! for! remaining! geometric! distortions!of!dMRI!data,!two!similarity!measures!with!equal!weight!were!used:! mutual!information!between!the!T1!image!and!average!of!the!b=1000!DWIs,!and! cross!correlation!between!T1!WM!and!the!FA!image.!Finally,!all!the!MET2!as!well! as!WM!tissue!segmentations,!DTI,!DKI!and!NODDI!native!parameter!maps!were! nonrigidly!normalized!to!the!group!template!using!an!affine!and!non%rigid!DTI% based! coregistration! algorithm! (Leemans! and! Jones,! 2009,Van! Hecke,! et! al.,! 2007).!
!
2.3.3!Construction!of!white!matter!masks! !
To!reduce!partial!volume!effects,!each!participant’s!image!was!multiplied! by! a! WM! mask! based! on! their! individual! thresholded! (0.8)! and! binarised! WM! tissue! map! obtained! from! the! SPM8! segmentation! of! their! native! T1! image.! As! such,!we!restricted!analysis!to!voxels!containing!at!least!80%!WM.!Furthermore! any! voxels! that! overlapped! with! the! “Automatic! lateral! ventricle! delineation”! (ALVIN)! ventricle! mask! were! excluded! (Kempton,! et! al.,! 2011).! Additionally,! another!WM!mask!was!applied!based!on!the!average!white!matter!segmentation! of! all! subjects,! thresholded! at! 0.8! and! binarised.! This! was! done! to! ensure! that! only! voxels! that! had! a! high! likelihood! of! being! WM! in! all! participants! were! incorporated.!Finally,!to!reduce!partial!volume!contamination!from!voxels!in!the! basal! ganglia! and! thalamus! regions,! an! exclusion! mask! was! applied! including! caudate,!putamen,!globus!pallidus!and!thalamus!ROIs!as!defined!by!the!Harvard% Oxford! cortical! and! subcortical! structural! atlas! (Frazier,! et! al.,! 2005).! The! final! mask!is!visible!in!Figure!1!and!in!more!detail!in!Supplementary!Figure!1!and!2.! !
!
2.4'Data'analysis'
For! assessing! the! correlation! of! all! metrics! with! age! in! well%defined! regions!of!interest!(ROIs),!we!used!the!Johns!Hopkins!University!(JHU)!WM!atlas! labels!(Mori,!et!al.,!2005).!For!each!participant,!the!mean!metric!value!of!voxels! inside!a!ROI!was!calculated,!excluding!the!lowest!2%!and!highest!2%!of!values.! Because!the!3D!GraSE!sequence!has!a!limited!FOV,!metrics!were!only!evaluated! in!those!regions!for!which!all!participants!had!data!in!more!than!half!of!the!ROI! (i.e.! all! brainstem! and! cerebellum! regions! were! excluded).! To! reduce! multiple! comparisons,! the! analysis! combined! bilateral! structures! into! single! regions! (n=23).!This!was!deemed!acceptable!because!age%related!differences!have!been! shown! to! occur! predominantly! bilaterally! (Callaghan,! et! al.,! 2014,Draganski,! et! al.,!2011,Lebel,!et!al.,!2012,Salat,!et!al.,!2005).!Also!small!ROIs!(mean!–!standard! deviation!less!than!100!voxels)!were!excluded!from!the!analysis!to!avoid!ROI!size! bias.! These! included! the! tapetum,! uncinate! fasciculus,! superior! fronto%occipital! fascicles,!the!cingulum!near!the!hippocampus!(separate!from!the!cingulum!near! the! cingulate! gyrus)! and! the! fornix! body! (separate! from! the! larger! fornix! crescent/stria! terminalis).! The! remaining! ROIs! and! their! size! in! voxels! are! summarized!in!Supplementary!Table!1.!
!
The! resulting! mean! metric! values! inside! ROIs! and! whole! cerebrum! WM! were! then! assessed! for! their! linear! and! quadratic! correlation! with! age! and! the! shared! variance! between! any! two! metrics! was! computed.! Correlations! were! deemed! significant! if! the! resulting! p%value! was! below! 0.05! after! correcting! for! multiple! comparisons! using! the! Holm%Bonferroni! method! for! family%wise! error! (FWE).!The!Steiger!z%test!was!applied!to!assess!whether!there!was!a!significant! difference!(pS<0.05)!between!linear!and!quadratic!correlation!with!age!for!each! ROI!and!metric.! ! 2.4.2!Voxel%wise!analysis! !
Statistical! analyses! were! carried! out! on! smoothed! parameter! maps! (FWHM=6mm)!in!population!atlas!space!using!mass%univariate!linear!regression! as! embedded! in! the! general! linear! model! framework! of! SPM8! (statistical!
http://www.fil.ion.ucl.ac.uk/spm/software/spm8/,! London,! United! Kingdom)! with!age!as!a!regressor.!2%tailed!t%!tests!were!used!to!look!for!differences!in!15! MRI%based!measures!with!age:!DTI!metrics!(FA,!MD,!AD,!RD),!DKI!metrics!(KA,! MK,! RK! AK),! NODDI! metrics! (NDI,! ODI,! FISO)! and! MET2! metrics! (MWF,! IEWF,! IEW%gmT2,! G%gmT2).! An! explicit! mask! limited! the! analysis! to! the! average! WM! mask!also!used!in!ROI!analysis!(i.e.!average!of!WM!tissue!maps!thresholded!at! 0.8,!binarised!and!excluding!basal!ganglia,!thalamus!and!lateral!ventricles).!!!
!
Additionally,! we! performed! a! voxel%based! morphometry! analysis! using! “diffeomorphic! anatomical! registration! through! exponentiated! Lie! algebra”! (DARTEL)!(Ashburner,!2007),!investigating!the!correlation!of!WM!volume!with! age,!expressed!as!a!T%score.!This!was!performed!on!smoothed!(FWHM!=!6mm)! modulated! normalized! WM! maps! in! MNI! space! generated! from! the! standard! SPM8! DARTEL! pipeline.! Total! WM! was! calculated! using! the! SPM! get_totals! script2.!!
In! all! SPM! analyses,! family%wise! error! was! controlled! using! an! FWE! threshold! of! p=0.05! and! clusters! surviving! this! threshold! were! deemed! significant!below!pFWE=0.05!at!cluster%level.!!
!
3.'Results' '
3.1'RegionCofCinterest'analysis' !
Figure! 3! illustrates! the! linear! correlation! of! DTI,! DKI,! NODDI! and! MET2! metrics! with! age! in! WM! regions! and! in! the! cerebral! WM! (mask).! ROIs! and! metrics!are!ranked!according!to!the!mean!shared!variance!(R2)!with!age.!Regions!
are! ranked! from! top! to! bottom! according! to! average! shared! variance! across! metrics.! Results! for! the! total! cerebral! WM! are! added! on! top! of! the! figure! for! comparison.!Metrics!are!ranked!from!left!to!right!according!to!average!R2!across!
ROIs.! Figure! 4! illustrates! the! correlation! coefficient! (i.e.! square! root! of! shared! variance)!for!quadratic!fit.!A!positive!sign!means!the!metric!vs.!age!relationship! !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
(a!parabola)!resembles!a!U%shaped!curve!while!negative!coefficients!indicate!an! inverse!U%shaped!curve.!
!
3.1.1!Regional!correlations! !
On! average! across! regions,! the! NODDI! measure! of! isotropic! diffusivity! (! FISO)! showed! the! largest! differences! with! age,! followed! by! neurite! dispersion! (ODI)! and! fractional! anisotropy! (FA).! In! some! regions,! a! quadratic! correlation! describes! the! data! significantly! better! than! a! linear! correlation.! These! region% metric! combinations! are! denoted! with! a! black! cell! border! in! Figure! 4.! As! an! example!the!curves!of!RD,!MK,!ODI!and!IEWF!in!selected!ROIs!are!illustrated!in! Figure!5.!
The!ROIs!that!show!the!strongest!correlation!with!age!on!average!across! metrics! were! the! fornix,! cerebral! peduncles,! external! capsules! and! the! genu! of! corpus!callosum.!The!least!strong!correlations!were!found!in!posterior!regions,! including!the!callosal!splenium.!
!
3.!1.!2!!Diffusion!metric!correlations!
The!NODDI!metrics!were!frequently!positively!correlated!with!age!across! the! regions! investigated.! FISO! showed! the! highest! correlation! with! age! in! the! external!capsules!(r!=!0.67,!pFWE!<!0.001)!followed!by!the!total!cerebral!WM!(r!=!
0.62,!pFWE!<!0.001),!suggesting!more!free!(isotropic)!diffusion!with!age.!This!is!
also!reflected!in!the!positive!correlations!of!MD!(in!cerebral!WM:!r!=!0.31,!pFWE!=!
0.005).! Figure! 4! shows! that! age%related! differences! of! FISO! and! all! diffusivities! (MD,!RD,!AD)!tend!to!express!a!U%shaped!pattern,!which!means!a!local!minimum! is! reached! after! which! values! increase.! The! sagittal! stratum! is! the! only! region! where!RD!and!MD!show!a!significantly!better!quadratic,!compared!to!linear!fit.!
Because!ODI!and!NDI!are!believed!to!represent!independent!aspects!of!FA! (Zhang,!et!al.,!2012)!we!group!results!from!these!metrics!here.!In!most!ROIs,!ODI! and! FA! show! similar! but! opposite! linear! correlation,! suggesting! reduced! anisotropy!with!increasing!age.!Figure!4!reveals!that!in!most!ROIs!where!both!FA! and! ODI! change! significantly,! the! curves! of! ODI! vs.! age! and! FA! vs.! age! are! opposite! to! each! other,! indicating! some! similarity! between! both.! The!
(predominantly!linear)!positive!correlation!of!NDI!with!age!furthermore!reflects! increasing! intracellular%like! signal! relative! to! the! extracellular%like! signal.! The! profiles!of!FA,!ODI!and!NDI!vs.!age!were!not!consistently!U%shaped!or!inverse!U% shaped!across!regions.!
Diffusion!kurtosis!metrics!revealed!less!age%related!differences!compared! to! DTI! and! NODDI! metrics.! Of! all! the! DKI! parameters,! AK! displayed! the! most! significant!correlation!with!age,!reflected!by!increasing!values!over!the!lifespan.! Mean! kurtosis! increased! most! significantly! in! the! anterior! limb! of! the! internal! capsules! (r! =! 0.50,! pFWE! =! 0.012)! and! presented! inverse! U%shaped! profiles.!
Differences!in!RK!and!KA!were!too!small!to!reveal!the!shape!of!quadratic!fitted! curves,!as!only!few!ROIs!yielded!above!threshold!correlation!coefficients.!! ! 3.1.3!!MET2!metric!correlations! Compared!to!diffusion!MRI!metrics,!the!differences!in!MET2!metrics!were! generally!smaller.!The!most!significant!differences!in!MET2!metrics!were!found! in! the! fornix! crescent/stria! terminalis.! In! this! structure! MWF! showed! a! trend! towards!a!linear!increase!(r!=!0.46,!pFWE!=!0.057)!and!IEWF!decreased!with!age!
as!a!U%shaped!curve!(r!=!%0.56,!pFWE!=!0.0074).!! '
3.2'Voxelwise'assessment'of'lifespan'effects' !
3.2.1!Whole!brain!correlations!!
There! was! no! significant! correlation! between! total! WM! volume! and! age! (linear:!r!=!%0.0094!(p!=!0.94),!quadratic:!r!=!%0.0034!(p!=!0.98)).!Results!from!our! voxel!based!morphometry!DARTEL!analysis!additionally!revealed!no!statistically! significant!regional!WM!volume!effects!at!the!selected!cluster%level!threshold!of! pFWE=0.05.! ! 3.2.2!Diffusion!MRI!metrics! ! DTI!
! Figure! 6! illustrates! regional! differences! in! FA,! MD,! RD! and! AD.! Effects! were!widespread!including!a!bilateral!anterior!reduction!in!FA!located!along!the!
frontal!projections!of!the!corpus!callosum!(T>5.28,!pFWE!<0.009!at!cluster%level).!
This!decreased!anisotropy!was!mainly!paralleled!by!an!increase!in!RD!(T>5.48,! pFWE<0.01!at!cluster!level)!and!less!by!MD!or!AD.!Anisotropy!was!decreased!and!
(mainly! radial)! diffusivity! increased! in! superior! parietal! WM! (corona! radiata)! and!regions!of!crossing!fibres!such!as!the!centrum!semiovale!(FA:!T!=!7.17,!pFWE! <!0.001;!RD:!T!=!7.41,!pFWE!<!0.001).!! ! DKI! ! Figure!7!illustrates!regional!differences!in!AK,!MK,!RK!and!KA.!There!were! substantially!fewer!age%related!differences!detected!using!DKI!compared!to!DTI.! Similar!to!MD,!MK!increased!with!age!in!the!corona!radiata!(T=7.40,!pFWE<0.001).!
In! contrast! to! DTI! where! RD! appeared! to! drive! the! increased! mean! diffusivity,! MK!was!more!paralleled!by!an!increase!in!AK!(T!=!7.42,!pFWE!<!0.001)!than!RK!(T!
=!6.44,!pFWE!=!0.001).!The!internal!capsules!furthermore!showed!a!trend!towards! increasing!MK!(T=4.25,!pFWE!=!0.022)! ! ! NODDI! Figure!8!illustrates!regional!differences!in!FISO,!ODI,!and!NDI.!The!most! significant! effects! were! widespread! increases! in! FISO! throughout! most! of! the! cerebral!WM,!including!the!corpus!callosum!body!and!corona!radiata,!but!with! only!limited!increases!in!the!occipital!lobe.!! ! Of!the!NODDI!metrics,!differences!in!NDI!were!smallest,!with!increases!in! the!posterior!corona!radiata.!Only!very!limited!differences!in!NDI!were!found!in! WM!of!the!frontal!lobe.!! !
ODI! on! the! other! hand! expressed! widespread! linear! increases! with! age! including!both!anterior!and!posterior!corona!radiata,!the!intersection!of!several! parietal! and! occipital! fiber! pathways,! (T! =! 7.84,! pFWE<0.001)! and! posterior!
thalamic!radiation!(T=!5.82,!pFWE<0.001).!
!
!
Figure!9!illustrates!regional!differences!in!MWF,!IEW%gmT2!and!G%gmT2.! Overall,! age%related! differences! were! minor! and! only! few! results! were! significant.!Mean!T2!time!(G%gmT2),!IEWF!and!IEW%gmT2!slightly!decreased!in! the!external!capsules!(T!=!5.76%6.27,!pFWE!=!0.001!–!0.004)!
There! was! a! trend! towards! an! overlapping! increase! in! MWF! and! decrease! in! IEWF!and!G%gmT2!(but!not!IEW%gmT2)!in!the!midbrain!(T!=!4.22!–!5.39,!pFWE=!
0.012! %! 0.23).! Minor! increases! of! all! MET2! metrics! were! found! in! the! corona! radiata! and! of! IEW%gmT2! in! frontal! WM.! Notably,! unlike! with! the! diffusion! metrics,! MET2! metrics! displayed! both! increases! and! decreases! within! metrics,! which!may!reflect!changing!T2!properties!of!tissue!over!the!lifespan.!
'
3.'3'Correlation'between'metrics' '
Figure! 10! displays! the! shared! variance! (i.e.! the! square! of! the! linear! correlation! coefficient)! between! pairs! of! metrics! in! whole! cerebral! WM! illustrating! how! much! similar! or! unique! information! the! different! metrics! provide.!
!
As! expected,! DTI! metrics! have! a! high! proportion! of! shared! variance! among!themselves!(i.e.!intra%modal).!The!same!is!true!for!DKI!and!MET2,!while! NODDI!metrics!share!only!limited!variance!with!each!other!(FISO!vs.!ODI:!12%,! NDI! vs.! ODI:! 3%,! FISO! vs.! NDI:! 21%).! FISO,! being! an! indicator! for! isotropic! diffusivity,!correlated!strongly!with!MD!(31%),!RD!(30%)!and!AD!(20%),!which! also! quantify! isotropic! diffusion.! Across! whole! cerebral! WM,! the! measures! of! anisotropy!FA!and!ODI!showed!rather!strong!(negative)!correlations!with!each! other!resulting!in!36%!of!shared!variance.!In!contrast,!NDI!was!not!significantly! correlated!with!FA!(17%)!or!ODI!(3%).!MWF!and!IEWF!correlated!strongly!with! DKI!metrics!and!NDI,!but!not!with!DTI!measures.!!Similarly,!NDI!showed!higher! shared! variance! with! DKI! metrics! (in! particular! with! MK:! 89%)! than! with! DTI! metrics.!!
'
!
4.1!Summary! !
In! this! cross%sectional! study,! we! examined! the! relationship! between! multiple! diffusion! MRI! and! myelin%sensitive! MET2! “myelin%water! imaging”! measures! and! age! in! brain! WM! in! a! healthy! adult! population.! We! used! complementary! ROI! and! voxel%based! analyses,! and! examined! the! relationships! between! the! different! parameters! used! in! these! analyses.! Our! results! indicate! widespread!WM!microstructural!differences!in!the!absence!of!gross!WM!atrophy,! with!heterogeneous!regional!alterations!between!different!measures,!potentially! reflecting! different! aspects! of! microstructural! change! and! their! evolution! over! the! period! of! late! development! and! early! ageing.! Metrics! quantifying! Gaussian! diffusivity! (in! particular! FISO)! had! the! strongest! correlations! and! most! widespread! age%effects,! possibly! related! to! cerebrospinal! fluid! increase,! whilst! non%DTI!metrics!correlated!well!with!myelin!water!imaging!measures.!!
!
4.2!Study!findings!in!the!context!of!retrogenesis!and!(de)myelination! !
Our! results! are! in! agreement! with! previous! findings! of! an! age%related! decline! in! FA! that! is! more! pronounced! in! frontal! regions! (Bartzokis,! et! al.,! 2012,Davis,! et! al.,! 2009,Lebel,! et! al.,! 2012,Salat,! et! al.,! 2005)! and! which! may! reflect!an!anteroposterior!gradient!of!retrogenesis!(Bartzokis,!et!al.,!2012,Inano,! et! al.,! 2011,Kumar,! et! al.,! 2013,Lebel,! et! al.,! 2012,Madden,! et! al.,! 2004,Pfefferbaum,!et!al.,!2000,Salat,!et!al.,!2005).!In!this!process,!WM!fibers!that! were!myelinated!latest!during!development!(e.g.!genu!of!corpus!callosum)!have! thinner! myelin! sheaths! than! early! developing! WM! (e.g.! splenium! of! corpus! callosum)!and!therefore!degenerate!first!during!late!adulthood!and!senescence.!!
Although! controversial! (Wheeler%Kingshott! and! Cercignani,! 2009),! changes!in!RD!have!been!associated!with!changes!in!the!myelin!sheath!(Song,!et! al.,!2005).!The!age%related!decrease!in!FA!and!increase!in!MD!we!detected!were! indeed!accompanied!by!a!more!significant!increase!of!RD!than!AD!suggesting!a! myelin%related! contribution! to! FA! decrease.! However,! our! results! from! myelin! water! imaging! run! somewhat! counter! to! the! demyelination! hypothesis! as! we!
detected! positive,! not! negative! linear! correlations! between! age! and! MWF,! in! agreement! with! Flynn! et! al.! (Flynn,! et! al.,! 2003).! The! low! shared! variance! between!MWF!and!FA!in!our!study!indicates!that!age%related!FA!changes!do!not! necessarily!correspond!to!changes!in!myelin!content.!This!is!in!line!with!previous! (non%aging)!findings!showing!little!correlation!between!FA!and!myelin!measures! (Beaulieu,! 2002,Beaulieu! and! Allen,! 1994,De! Santis,! et! al.,! 2014,Madler,! et! al.,! 2008).!Furthermore,!other!metrics!that!are!sensitive!for!tissue!fractions!(IEWF,! NDI)!or!compartmentalization!(kurtosis!metrics)!did!not!show!large!age%related! differences!in!frontal!WM.!
This!begs!the!question!of!what!actually!drives!the!decrease!in!frontal!FA,! if! it! is! not! demyelination.! Figure! 8! has! shown! us! a! frontal! increase! in! neurite! dispersion! (ODI)! as! modeled! by! the! NODDI! framework.! Moreover,! throughout! the! WM,! ODI! shared! 36%! of! variance! with! FA! (Figure! 10).! Although! highly! speculative,!these!combined!findings!suggest!that!rather!than!demyelination!or! alterations!in!tissue!compartmentalization,!increased!axonal!disperion!may!drive! the! earliest! decreases! in! frontal! FA.! In! line! with! this! argument,! a! study! investigating!the!correlation!of!similar!(but!not!the!same)!MET2!and!multi%shell! dMRI! metrics! in! a! young! cohort! (mean! age/standard! deviation!=!24.2/2.8! yrs)!found! that! DTI! measures! are! more! dependent! on! the! underlying! microarchitectural! paradigm! (e.g.! presence/number! of! crossing%fibers)! than! metrics!based!on!multicompartment!models!(De!Santis,!et!al.,!2014).!!
!
4.3!Kurtosis!metrics!and!NDI!may!reveal!signs!of!late!maturation.!! !
The!VBA!and!ROI!results!finding!positive!correlations!of!age!with!MK!and! RK! diverge! from! previous! studies! in! which! negative! correlations! were! found! (Coutu,!et!al.,!2014,Gong,!et!al.,!2014,Latt,!et!al.,!2013).!Age%related!differences!in! AK! were! only! reported! in! (Coutu,! et! al.,! 2014)! and! in! contrast! to! our! findings! showed! negative! correlation! with! age.! This! could! be! explained! by! the! older! sample!in!the!Coutu!et!al.!study,!which!may!have!captured!the!phase!of!decline! while! our! sample! reflects! late! maturation! and! early! ageing.! Figure! 4! indeed! suggests!that!AK!and!MK!in!most!ROIs!follow!an!inverted!U%shaped!curve!which,! given! the! positive! linear! correlation! with! age! (Figure! 3),! goes! along! with! an!
initial!increase!(associated!with!ongoing!maturation)!and!subsequent!decline.!In! DTI! metrics! on! the! other! hand,! the! phase! of! reversal! seems! to! have! already! passed,!as!FA!continues!to!decrease!(inverted!U%shape)!and!diffusivities!continue! to! increase! (U%shape).! DTI! and! DKI! metrics! may! therefore! relate! to! different! dynamics!throughout!the!lifespan,!meaning!DTI!metrics!may!reveal!early!decline! through! the! linear! correlation! coefficients,! while! kurtosis! metrics! may! capture! signs!of!late!maturation.!!
Similar! to! kurtosis! metrics,! we! detected! an! increase! of! NDI! with! age! instead! of! an! expected! decrease.! The! pattern! of! age%related! differences! of! NDI! closely!resembled!that!of!kurtosis!metrics,!with!the!largest!clusters!in!superior! parietal!WM!(Figures!7,8)!and!a!trend!towards!an!inverted!U%shape!curve!in!total! cerebral! WM! (Figure! 4).! Furthermore! Figure! 10! has! shown! that! NDI! and! MK! correlate!very!strongly!and!have!89%!of!shared!variance,!suggesting!a!common! driving!factor.!One!possible!explanation!could!be!that!age%related!differences!in! non%Gaussian! diffusion! as! measured! by! MK! are! largely! driven! by! changes! to! axonal!density.!!!
!
4.4! MET2! metrics! are! less! sensitive! to! age%related! differences! during! early! to! mid%adulthood!than!diffusion!measures!
!
As!only!minor!differences!with!age!were!found!using!MET2,!it!may!be!less! suitable!for!studying!early!aging!effects!than!diffusion!MRI!and!DTI!and!NODDI! metrics! in! particular.! While! shared! variance! values! between! MET2! and! DTI! metrics! were! below! the! significance! threshold! (Figure! 10),! some! degree! of! similarity! was! detected! between! MET2,! DKI! and! NDI.! This! similarity! is! not! surprising!as!kurtosis!is!believed!to!reflect!the!degree!of!compartmentalization! (Hui,!et!al.,!2008),!!which!is!also!reflected!in!MWF,!IEWF!and!NDI.!!!
Interestingly,! in! ROIs! where! differences! in! MWF! were! detected,! the! correlation!with!age!was!positive,!suggesting!an!increase!in!myelin!content!with! age.! Although! in! agreement! with! Flynn! et! al.! (Flynn,! et! al.,! 2003),! this! is! counterintuitive.! In! this! context! it! is! important! to! keep! in! mind! that! MWF! and! IEWF!are!defined!as!a!ratio!relative!to!the!total!visible!T2!distribution.!An!age% related!increase!in!MWF!may!therefore!also!be!explained!by!an!absolute!loss!of!
IE!water.!An!age%related!decrease!of!MWF!may!indicate!both!demyelination!and! also!an!absolute!increase!of!IE!water!or!the!presence!of!an!additional!water!pool! with! T2! values! outside! both! myelin! and! IE! integration! windows! (i.e.! between! 200ms!and!2s).!The!latter!is!unlikely!to!be!present!in!the!current!study!sample!as! they! have! only! been! detected! in! pathologic! white! matter,! e.g.! in! case! of! phenylketonuria!(Laule,!et!al.,!2007b)!or!multiple!sclerosis!(Laule,!et!al.,!2007a).!!
!
4.5!Comparison!between!ROI!and!VBA!results! !
The! advantage! of! an! ROI! analysis! for! aging! studies! is! that! results! can! easily! be! localized! to! certain! specific! anatomical! regions! and! the! number! of! statistical!comparisons!may!be!reduced!relative!to!whole!brain!VBA!approaches.! Moreover,! the! introduction! of! smoothing! and! statistical! thresholds! means! that! changes! in! smaller! regions! such! as! the! fornix,! are! less! readily! detected! using! VBA.! One! would! expect! however,! that! the! greatest! regional! changes! would! be! detected! by! both! methods.! ! Indeed,! in! most! regions,! results! from! our! VBA! and! ROI! analysis! are! in! agreement.! There! were! however! some! exceptions.! For! example,! in! the! posterior! corona! radiata,! VBA! detected! subtle! differences! in! MET2!metrics,!MD!and!AD!that!were!not!detected!in!the!ROI!analysis.!This!could! be!due!to!ROIs!not!capturing!as!much!WM!in!this!region!as!well!as!differential! partial!volume!effects,!smoothing,!and!statistical!significance!thresholds!related! to!FWE!correction.!! ! 4.6!!Methodological!considerations! ' Our!results!are!largely!in!accordance!with!previous!MRI!findings!on!larger! populations! and! neurobiology.! The! age! range! of! our! participants! most! likely! captures! the! processes! of! late! development! and! early! neurodegeneration,! and! therefore!our!findings!may!be!less!comparable!to!studies!that!include!younger!or! older!participants.!For!example,!analyses!including!participants!over!and!under! 60! years! old! have! demonstrated! more! significant! decline! in! the! older! group! (Salat,!et!al.,!2005).!This!could!also!explain!why!we!did!not!find!any!significant! decrease! in! WM! volume! with! age,! and! why! some! parameters! did! not! display! a!
quadratic! correlation! with! age.! Because! WM! volume! (and! also! grey! matter! volume)! did! not! decrease! significantly,! we! did! not! include! brain! volume! as! a! covariate.!This!could!also!account!for!discrepancies!with!other!studies.!!
!
Undertaking!a!multimodal!multiparametric!analysis!such!as!in!this!study! necessarily! requires! multiple! image! registration! steps.! In! order! to! minimize! registration!errors,!we!used!a!population!atlas!based!approach!and!sophisticated! well%validated! non%linear! registration! methods! (Avants,! et! al.,! 2008),! and! assessed! registration! accuracy! at! each! stage! of! the! processing! and! analysis! pipeline.! However,! as! with! all! studies! of! this! type,! we! cannot! rule! out! the! contribution! of! subtle! registration,! interpolation! and! partial! volume! effects! to! our!findings!(Van!Hecke,!et!al.,!2011,Vos,!et!al.,!2011).!In!this!context,!although! we!did!not!detect!voxel%wise!correlations!between!age!and!WM!volume,!it!is!still! possible! that! the! associations! we! have! detected! reflect! age%related! macrostructural! changes! rather! than! changes! in! specific! microstructural! elements!such!as!myelin!content.!
!
Some!metrics!in!our!study!varied!with!age,!however,!correlation!does!not! imply!a!causal!relationship.!Other!factors!that!are!not!related!to!age!such!as!IQ! may! have! an! influence! on! these! metrics.! We! did! not! explicitly! test! IQ! in! this! sample;!however,!there!were!no!differences!in!educational!level!across!the!age% range! studied.! Participants! of! different! ages! were! also! randomly! scanned,! reducing!the!influence!of!scanner!changes!over!time.!!
!
In! vivo! MRI! metrics! are! indirect! measures! based! on! averaging! multiple! tissue! properties! over! voxels! many! times! larger! than! the! structures! that! are! being! probed.! Whilst! the! various! metrics! are! described! in! terms! of! biological! properties!such!as!intra!and!extracellular!water,!or!myelin,!in!reality!these!labels! are! based! on! mathematical! models! as! applied! to! imperfect! MRI! data.! ! We! detected!a!number!of!counterintuitive!findings!in!this!context.!For!example,!NDI! (reflecting! neurite! density),! increased! with! age.! This! highlights! the! need! for! further! basic! research! into! the! neurobiological! correlates! of! diffusion! MRI! and! MET2!measures!as!the!models!are!influenced!by!other!tissue!properties!beyond!
those!the!metrics!attempt!to!characterize.!For!example,!WM!regions!in!the!deep! WM! and! the! midbrain! are! close! to! structures! that! contain! iron! or! accumulate! iron! with! age! (Callaghan! et! al,! 2014).! Iron! influences! the! T2! relaxation! signal,! which!underlies!all!the!metrics!assessed!in!this!study.!!
!
5.!Conclusion! !
Using! advanced! diffusion! MRI! and! multi%exponential! T2! relaxation! we! found!age%related!differences!in!multiple!MRI!measures!of!microstructure!across! the!brain!WM!that!predate!atrophy.!Commonly!reported!frontal!WM!decreases!in! FA! may! not! reflect! demyelination,! but! an! increase! in! axonal! dispersion.! The! correlation!between!MET2,!DKI!metrics!and!neurite!density!(NDI)!suggests!they! may! be! sensitive! to! similar! microstructural! features,! whilst! DTI! and! NODDI! appear!to!be!most!sensitive!to!lifespan!effects!in!young!to!mid%adulthood.!
Further!research!into!the!underlying!biological!basis!of!novel!MRI!based! measures!is!required,!however!this!study!clearly!demonstrates!the!added!value! of! using! multimodal! multiparametric! MRI! data! for! assessing! age%related! WM! microstructural!differences.! ! Acknowledgements.''' ' The!authors!would!like!to!thank!Frederik!Dekeyzer!for!valuable!discussions!on! statistical!theory,!Marjolein!Verly!for!help!with!scanning!and!all!our!volunteers! for!their!participation.!
This! research! was! supported! by! funding! from! the! European! Union! Seventh! Framework!Programme!under!grant!agreement!279281!(TB,!BVdB),!KU!Leuven,! PFV/10/008! grant! (LE,! MV,! SS)! and! KU! Leuven! international! mobility! bursary! (LE).! ! Disclosure'statement' ! The!authors!have!no!actual!or!potential!conflicts!of!interest.! !
Figure'and'table'legends' !
Figure!1.!
Image! processing! pipeline! used! in! the! current! study.! Aff.! =! Affine,! Diff.! =! diffeomorphic,!MI!=!mutual!information,!CC!=!cross!correlation,!NR!=!non%rigid.!! !
Figure!2.!!
Parameter! maps! obtained! from! a! single! participant! in! template! space.! FA:! fractional! anisotropy;! MD:! mean! diffusivity! (mm2/s);! RD:! radial! diffusivity!
(mm2/s);! AD:! axial! diffusivity! (mm2/s);! KA:! kurtosis! anisotropy;! MK:! mean!
kurtosis;! RK:! radial! kurtosis;! AK:! axial! kurtosis;! MWF:! myelin! water! fraction;! IEWF:! intra%! and! extracellular! water! fraction;! IEW%gmT2:! geometric! mean! T2! time! of! intra%and! extracellular! water! (s);! G%gmT2:! geometric! mean! T2! time! of! general! T2! distribution! (s);! NDI:! neurite! density! index;! ODI:! orientation! dispersion!index;!FISO:!isotropic!fraction!
!
Figure!3.!!
Linear!correlation!coefficients!of!metrics!with!age.!Cell!values!in!black!represent! correlation! coefficients! that! are! significant! (p<0.05)! at! uncorrected! level.! Cell! values!in!white!represent!correlation!coefficients!that!are!significant!(pFWE<0.05)! after!controlling!the!family%wise!error.! The!order!of!ROIs!and!metrics!depends! on!the!mean!R2!of!linear!(standard)!or!quadratic!fit!(if!significantly!better):!ROIs! are!ranked!in!order!of!decreasing!mean!R2!across!metrics!and!metrics!are!ranked! in!descending!order!of!mean!R2!across!ROIs.!The!color!labels!correspond!to!the! JHU!ROIs!used!for!analysis,!as!illustrated!on!the!axial!brain!slices!(below).! ! Figure!4.!! Quadratic!correlation!coefficients!of!metrics!with!age.!A!positive!sign!indicates!U% shaped! curve! and! a! negative! sign! indicates! an! inverse! U%shaped! curve.! Cell! values!in!black!represent!correlation!coefficients!that!are!significant!(p<0.05)!at! uncorrected!level.!Cell!values!in!white!represent!correlation!coefficients!that!are! significant!(pFWE<0.05)!after!controlling!the!family%wise!error.!Cells!with!a!black!
Figure! 3.! For! comparison,! ROIs! and! metrics! are! ranked! in! the! same! way! as! in! Figure! 3.! The! color! labels! correspond! to! the! JHU! ROIs! used! for! analysis,! as! illustrated!on!the!axial!brain!slices!(below).!
! !
Figure!5.!!
Scatter!plots!illustrating!ROIs!where!quadratic!fit!with!age!is!significantly!better! than! a! linear! fit! (red! =! female,! blue! =! male).! Panel! A:! intra%! and! extracellular! water! fraction! in! the! fornix! stria! terminalis! increases! again! with! age! after! a! minimum! is! reached! between! 40! and! 50! years! of! age.! Panel! B:! ! Orientation! dispersion!of!neurites!in!the!retrolenticular!part!of!the!internal!capsule.!Panel!C:! Radial!diffusivity!in!the!sagittal!stratum.!D:!Mean!kurtosis!in!the!anterior!limbs!of! the!internal!capsule! ! Figure!6.!! Statistical!parametric!maps!from!voxel%based!linear!regression!of!WM!diffusion! tensor!parameters!with!age.!FA:!fractional!anisotropy,!MD:!mean!diffusivity,!RD:! radial! diffusivity,! AD:! axial! diffusivity.! The! blue! color! scale! indicates! negative! correlation!(r<0)!with!age.!The!red!scale!indicates!positive!correlation!(r>0)!with! age.! DTI! metrics! reveal! increasing! isotropic! diffusion! with! the! most! significant! differences!in!frontal!WM.!
!
Figure!7.!
Statistical! parametric! maps! from! voxel%based! linear! regression! of! WM! kurtosis! parameters! with! age.! KA:! kurtosis! anisotropy,! MK:! mean! kurtosis,! RK:! radial! kurtosis,! AK:! axial! kurtosis.! The! blue! color! scale! indicates! negative! correlation! with! age.! The! red! scale! indicates! positive! correlation! with! age.! DKI! metrics! showed! minor! but! widespread! differences! with! age.! The! most! significant! differences!were!found!in!regions!near!the!corona!radiata.!
!
Figure!8.!
Statistical! parametric! maps! from! voxel%based! linear! regression! of! WM! NODDI! parameters! with! age.! FISO:! isotropic! fraction,! NDI:! neurite! density! index,! ODI:!
orientation! dispersion! index.! The! red! scale! indicates! positive! correlation! with! age.!NODDI!metrics!reveal!a!large!and!widespread!increase!in!isotropic!diffusion.! NDI!expressed!increased!neurite!density!mainly!in!superior!parietal!WM!(corona! radiata).! Differences! in! ODI! were! located! in! frontal! WM,! superior! parietal! WM! and!regions!of!crossing!white!matter!pathways.!!
!
Figure!9.!
Statistical! parametric! maps! from! voxel%based! linear! regression! of! WM! MET2! parameters!with!age.!MWF:!myelin!water!fraction,!IEWF:!intra%and!extracellular! water! fraction,! IEW%gmT2:! geometric! mean! T2! time! of! intra%! and! extracellular! water,! G%gmT2:! geometric! mean! T2! time! of! general! T2! distribution.! The! blue! color! scale! indicates! negative! correlation! with! age.! The! red! scale! indicates! positive! correlation! with! age.! MWF! did! not! change! significantly! in! frontal! WM! but!in!parallel!with!IEWF!showed!largest!differences!in!the!midbrain.!IEW%gmT2! and!to!a!less!extent!G%gmT2!showed!frontal!and!superior!parietal!increases!with! age.!!
!
Figure!10.!!
The! shared! variance! of! metric! values! averaged! over! the! cerebral! WM! mask! expressed!as!a!percentage!(The!higher!the!shared!variance!between!two!metrics,! the!better!differences!in!one!metric!explain!differences!in!the!other!metric).!Red! and! blue! color! scales! additionally! indicate! whether! two! metrics! are! positively! (r>0)! or! negatively! (r<0)! correlated,! respectively.! Non%significant! values,! controlling!the!family%wise!error!at!p=0.05!level,!are!displayed!in!grey.!Kurtosis! metrics! (AK,! MK,! RK,! KA)! and! NDI! correlated! well! with! MWF! and! IEWF.! Mean! kurtosis!correlated!well!with!neurite!density!index!
!
Table!1!
Summary!of!metrics!used!in!this!study.!Adapted!from!(Billiet,!et!al.,!2014a).!Panel! A)! Summary! of! dMRI! techniques,! models! and! derived! parameters! used! in! the! present! study.! FA! =! fractional! anisotropy,! MD! =! mean! diffusivity,! RD! =! radial! diffusivity,!AD!=!axial!diffusivity,!MK!=!mean!kurtosis,!RK!=!radial!kurtosis,!AK!=! axial!kurtosis,!KA!=!kurtosis!anisotropy,!FISO!=!isotropic!fraction,!NDI!=!neurite!
density!index,!ODI!=!!orientation!dispersion!index.!Panel!B)!Summary!of!myelin! water!imaging!model!and!derived!parameters!used!in!the!present!study.!MWF!=! myelin!water!fraction,!IEWF!=!intra%!and!extracellular!water!fraction,!IEW%gmT2! =!geometric!mean!T2!time!of!intra%!and!extracellular!water,!G%gmT2!=!geometric! mean!T2!time!of!general!T2!distribution! ! ! Supplementary!Table!1:!!
Mean! size! and! standard! deviation! of! total! cerebral! WM! and! regions! of! interest! from! John! Hopkins! University! white! matter! atlas! (Mori,! et! al.,! 2005)! after! applying!WM!masks!as!described!in!section!2.3.3.!
!
Supplementary!Figure!1!
Percentage!of!overlap!of!each!individual’s!white!matter!mask.!Values!represent! the! frequency! that! a! voxel! of! the! WM! mask! as! described! in! section! 2.3.3! was! classified!as!white!matter!across!participants!(i.e.!individual!segmentation!higher! than!0.8)!!!
!
Supplementary!Figure!2!
Comparison! of! ‘youngest’! and! ‘oldest’! white! matter! masks.! Red! =! mean! white! matter! segmentation! of! six! youngest! participants! (age! =! 19.2! ±! 1;! 3! males)! thresholded! at! 0.8.! Green! =! mean! white! matter! segmentation! of! six! oldest! participants! (age! =! 62.3! ±24;! 3! males).! Blue! =! overlap! between! white! matter! masks! of! both! subgroups.! A! large! overlap! is! seen! throughout! the! white! matter! illustrating!little!age%related!differences!due!to!registration.!
References' !
Ashburner,! J.! 2007.! A! fast! diffeomorphic! image! registration! algorithm.! Neuroimage! 38(1),! 95%113.! doi:10.1016/j.neuroimage.2007.07.007.!
Avants,! B.B.,! Epstein,! C.L.,! Grossman,! M.,! Gee,! J.C.! 2008.! Symmetric! diffeomorphic! image! registration! with! cross%correlation:! evaluating! automated! labeling! of! elderly! and! neurodegenerative! brain.! Med! Image!Anal!12(1),!26%41.!doi:10.1016/j.media.2007.06.004.!
Bartzokis,! G.,! Lu,! P.H.,! Heydari,! P.,! Couvrette,! A.,! Lee,! G.J.,! Kalashyan,! G.,! Freeman,! F.,! Grinstead,! J.W.,! Villablanca,!P.,!Finn,!J.P.,!Mintz,!J.,!Alger,!J.R.,!Altshuler,!L.L.!2012.!Multimodal!Magnetic!Resonance! Imaging!Assessment!of!White!Matter!Aging!Trajectories!Over!the!Lifespan!of!Healthy!Individuals.! Biol!Psychiatry.!doi:10.1016/j.biopsych.2012.07.010.! Basser,!P.J.,!Mattiello,!J.,!LeBihan,!D.!1994.!Estimation!of!the!effective!self%diffusion!tensor!from!the!NMR!spin! echo.!J!Magn!Reson!B!103(3),!247%54.! Beaulieu,!C.!2002.!The!basis!of!anisotropic!water!diffusion!in!the!nervous!system!%!a!technical!review.!NMR! Biomed!15(7%8),!435%55.!doi:10.1002/nbm.782.! Beaulieu,!C.,!Allen,!P.S.!1994.!Determinants!of!anisotropic!water!diffusion!in!nerves.!Magnetic!resonance!in! medicine!:!official!journal!of!the!Society!of!Magnetic!Resonance!in!Medicine!/!Society!of!Magnetic! Resonance!in!Medicine!31(4),!394%400.! Billiet,!T.,!Madler,!B.,!D'Arco,!F.,!Peeters,!R.,!Deprez,!S.,!Plasschaert,!E.,!Leemans,!A.,!Zhang,!H.,!den!Bergh,!B.V.,! Vandenbulcke,!M.,!Legius,!E.,!Sunaert,!S.,!Emsell,!L.!2014a.!Characterizing!the!microstructural!basis! of!"unidentified!bright!objects"!in!neurofibromatosis!type!1:!A!combined!in!vivo!multicomponent! T2! relaxation! and! multi%shell! diffusion! MRI! analysis.! Neuroimage! Clin! 4,! 649%58.! doi:10.1016/j.nicl.2014.04.005.!
Billiet,!T.,!Madler,!B.,!D'Arco,!F.,!Peeters,!R.,!Deprez,!S.,!Plasschaert,!E.,!Leemans,!A.,!Zhang,!H.,!den!Bergh,!B.V.,! Vandenbulcke,!M.,!Legius,!E.,!Sunaert,!S.,!Emsell,!L.!2014b.!Characterizing!the!microstructural!basis! of!"unidentified!bright!objects"!in!neurofibromatosis!type!1:!A!combined!in!vivo!multicomponent! T2! relaxation! and! multi%shell! diffusion! MRI! analysis.! Neuroimage! Clin! 4,! 649%58.! doi:10.1016/j.nicl.2014.04.005.!
Brickman,!A.M.,!Meier,!I.B.,!Korgaonkar,!M.S.,!Provenzano,!F.A.,!Grieve,!S.M.,!Siedlecki,!K.L.,!Wasserman,!B.T.,! Williams,! L.M.,! Zimmerman,! M.E.! 2012.! Testing! the! white! matter! retrogenesis! hypothesis! of! cognitive!aging.!Neurobiol!Aging!33(8),!1699%715.!doi:10.1016/j.neurobiolaging.2011.06.001.! Callaghan,! M.F.,! Freund,! P.,! Draganski,! B.,! Anderson,! E.,! Cappelletti,! M.,! Chowdhury,! R.,! Diedrichsen,! J.,!
Fitzgerald,! T.H.,! Smittenaar,! P.,! Helms,! G.,! Lutti,! A.,! Weiskopf,! N.! 2014.! Widespread! age%related! differences! in! the! human! brain! microstructure! revealed! by! quantitative! magnetic! resonance! imaging.!Neurobiol!Aging!35(8),!1862%72.!doi:10.1016/j.neurobiolaging.2014.02.008.!
Coutu,! J.P.,! Chen,! J.J.,! Rosas,! H.D.,! Salat,! D.H.! 2014.! Non%Gaussian! water! diffusion! in! aging! white! matter.! Neurobiol!Aging!35(6),!1412%21.!doi:10.1016/j.neurobiolaging.2013.12.001.! Davis,!S.W.,!Dennis,!N.A.,!Buchler,!N.G.,!White,!L.E.,!Madden,!D.J.,!Cabeza,!R.!2009.!Assessing!the!effects!of!age! on!long!white!matter!tracts!using!diffusion!tensor!tractography.!Neuroimage!46(2),!530%41.! De!Santis,!S.,!Drakesmith,!M.,!Bells,!S.,!Assaf,!Y.,!Jones,!D.K.!2014.!Why!diffusion!tensor!MRI!does!well!only! some!of!the!time:!variance!and!covariance!of!white!matter!tissue!microstructure!attributes!in!the! living!human!brain.!Neuroimage!89,!35%44.!doi:10.1016/j.neuroimage.2013.12.003.!
Deoni,! S.C.,! Dean,! D.C.,! 3rd,! O'Muircheartaigh,! J.,! Dirks,! H.,! Jerskey,! B.A.! 2012.! Investigating! white! matter! development! in! infancy! and! early! childhood! using! myelin! water! faction! and! relaxation! time! mapping.!Neuroimage!63(3),!1038%53.!doi:10.1016/j.neuroimage.2012.07.037.!
Draganski,!B.,!Ashburner,!J.,!Hutton,!C.,!Kherif,!F.,!Frackowiak,!R.S.,!Helms,!G.,!Weiskopf,!N.!2011.!Regional! specificity! of! MRI! contrast! parameter! changes! in! normal! ageing! revealed! by! voxel%based! quantification!(VBQ).!Neuroimage!55(4),!1423%34.!doi:10.1016/j.neuroimage.2011.01.052.! Falangola,!M.F.,!Jensen,!J.H.,!Babb,!J.S.,!Hu,!C.,!Castellanos,!F.X.,!Di!Martino,!A.,!Ferris,!S.H.,!Helpern,!J.A.!2008.!
Age%related!non%Gaussian!diffusion!patterns!in!the!prefrontal!brain.!J!Magn!Reson!Imaging!28(6),! 1345%50.!doi:10.1002/jmri.21604.!
Fjell,!A.M.,!Westlye,!L.T.,!Amlien,!I.,!Espeseth,!T.,!Reinvang,!I.,!Raz,!N.,!Agartz,!I.,!Salat,!D.H.,!Greve,!D.N.,!Fischl,! B.,! Dale,! A.M.,! Walhovd,! K.B.! 2009.! High! consistency! of! regional! cortical! thinning! in! aging! across! multiple!samples.!Cereb!Cortex!19(9),!2001%12.!doi:10.1093/cercor/bhn232.!
Flynn,!S.W.,!Lang,!D.J.,!Mackay,!A.L.,!Goghari,!V.,!Vavasour,!I.M.,!Whittall,!K.P.,!Smith,!G.N.,!Arango,!V.,!Mann,! J.J.,! Dwork,! A.J.,! Falkai,! P.,! Honer,! W.G.! 2003.! Abnormalities! of! myelination! in! schizophrenia! detected! in! vivo! with! MRI,! and! post%mortem! with! analysis! of! oligodendrocyte! proteins.! Mol! Psychiatry!8(9),!811%20.!doi:10.1038/sj.mp.4001337.!
Frazier,!J.A.,!Chiu,!S.,!Breeze,!J.L.,!Makris,!N.,!Lange,!N.,!Kennedy,!D.N.,!Herbert,!M.R.,!Bent,!E.K.,!Koneru,!V.K.,! Dieterich,! M.E.,! Hodge,! S.M.,! Rauch,! S.L.,! Grant,! P.E.,! Cohen,! B.M.,! Seidman,! L.J.,! Caviness,! V.S.,! Biederman,!J.!2005.!Structural!brain!magnetic!resonance!imaging!of!limbic!and!thalamic!volumes! in! pediatric! bipolar! disorder.! The! American! journal! of! psychiatry! 162(7),! 1256%65.! doi:10.1176/appi.ajp.162.7.1256.!
Gong,!N.J.,!Wong,!C.S.,!Chan,!C.C.,!Leung,!L.M.,!Chu,!Y.C.!2014.!Aging!in!deep!gray!matter!and!white!matter! revealed! by! diffusional! kurtosis! imaging.! Neurobiol! Aging! 35(10),! 2203%16.! doi:10.1016/j.neurobiolaging.2014.03.011.!
Haroutunian,! V.,! Katsel,! P.,! Roussos,! P.,! Davis,! K.L.,! Altshuler,! L.L.,! Bartzokis,! G.! 2014.! Myelination,! oligodendrocytes,!and!serious!mental!illness.!Glia.!doi:10.1002/glia.22716.!
Hennig,!J.!1988.!Multiecho!Imaging!Sequences!with!Low!Refocusing!Flip!Angles.!J!Magn!Reson!78(3),!397% 407.!doi:Doi!10.1016/0022%2364(88)90128%X.!
Hui,! E.S.,! Cheung,! M.M.,! Qi,! L.,! Wu,! E.X.! 2008.! Towards! better! MR! characterization! of! neural! tissues! using! directional! diffusion! kurtosis! analysis.! Neuroimage! 42(1),! 122%34.! doi:10.1016/j.neuroimage.2008.04.237.!
Inano,! S.,! Takao,! H.,! Hayashi,! N.,! Abe,! O.,! Ohtomo,! K.! 2011.! Effects! of! age! and! gender! on! white! matter! integrity.!AJNR!Am!J!Neuroradiol!32(11),!2103%9.!doi:10.3174/ajnr.A2785.!
Irfanoglu,!M.O.,!Walker,!L.,!Sarlls,!J.,!Marenco,!S.,!Pierpaoli,!C.!2012.!Effects!of!image!distortions!originating! from! susceptibility! variations! and! concomitant! fields! on! diffusion! MRI! tractography! results.! Neuroimage!61(1),!275%88.!doi:10.1016/j.neuroimage.2012.02.054.!
Jelescu,!I.O.,!Veraart,!J.,!Adisetiyo,!V.,!Milla,!S.S.,!Novikov,!D.S.,!Fieremans,!E.!2015.!One!diffusion!acquisition! and!different!white!matter!models:!How!does!microstructure!change!in!human!early!development! based!on!WMTI!and!NODDI?!Neuroimage!107,!242%56.!doi:10.1016/j.neuroimage.2014.12.009.! Jensen,! J.H.,! Helpern,! J.A.! 2010.! MRI! quantification! of! non%Gaussian! water! diffusion! by! kurtosis! analysis.!
NMR!Biomed!23(7),!698%710.!doi:10.1002/nbm.1518.!
Jensen,! J.H.,! Helpern,! J.A.,! Ramani,! A.,! Lu,! H.,! Kaczynski,! K.! 2005.! Diffusional! kurtosis! imaging:! the! quantification!of!non%gaussian!water!diffusion!by!means!of!magnetic!resonance!imaging.!Magnetic! resonance!in!medicine!:!official!journal!of!the!Society!of!Magnetic!Resonance!in!Medicine!/!Society! of!Magnetic!Resonance!in!Medicine!53(6),!1432%40.!doi:10.1002/mrm.20508.!
Jones,! D.K.,! Cercignani,! M.! 2010.! Twenty%five! pitfalls! in! the! analysis! of! diffusion! MRI! data.! NMR! Biomed! 23(7),!803%20.!doi:10.1002/nbm.1543.!
Kempton,!M.J.,!Underwood,!T.S.,!Brunton,!S.,!Stylios,!F.,!Schmechtig,!A.,!Ettinger,!U.,!Smith,!M.S.,!Lovestone,!S.,! Crum,! W.R.,! Frangou,! S.,! Williams,! S.C.,! Simmons,! A.! 2011.! A! comprehensive! testing! protocol! for! MRI! neuroanatomical! segmentation! techniques:! Evaluation! of! a! novel! lateral! ventricle! segmentation!method.!Neuroimage!58(4),!1051%9.!doi:10.1016/j.neuroimage.2011.06.080.! Kumar,!R.,!Chavez,!A.S.,!Macey,!P.M.,!Woo,!M.A.,!Harper,!R.M.!2013.!Brain!axial!and!radial!diffusivity!changes!
with!age!and!gender!in!healthy!adults.!Brain!Res!1512,!22%36.!doi:10.1016/j.brainres.2013.03.028.! Kunz,! N.,! Zhang,! H.,! Vasung,! L.,! O'Brien,! K.R.,! Assaf,! Y.,! Lazeyras,! F.,! Alexander,! D.C.,! Huppi,! P.S.! 2014.! Assessing! white! matter! microstructure! of! the! newborn! with! multi%shell! diffusion! MRI! and!
biophysical! compartment! models.! Neuroimage! 96,! 288%99.!
doi:10.1016/j.neuroimage.2014.03.057.!
Lally,!P.,!Zhang,!H.,!Pauliah,!S.,!Price,!D.,!Bainbridge,!A.,!Balraj,!G.,!Cady,!E.,!Shankaran,!S.,!Thayyil,!S.!2014.!8.9! Microstructural! Changes! in! Neonatal! Encephalopathy! Revealed! with! the! Neurite! Orientation! Dispersion!and!Density!Imaging!(NODDI)!Model.!Arch!Dis!Child!Fetal!Neonatal!Ed!99!Suppl!1,!A14.! doi:10.1136/archdischild%2014%306576.38.!
Latt,! J.,! Nilsson,! M.,! Wirestam,! R.,! Stahlberg,! F.,! Karlsson,! N.,! Johansson,! M.,! Sundgren,! P.C.,! van! Westen,! D.! 2013.!Regional!values!of!diffusional!kurtosis!estimates!in!the!healthy!brain.!J!Magn!Reson!Imaging! 37(3),!610%8.!doi:10.1002/jmri.23857.!
Laule,! C.,! Vavasour,! I.M.,! Kolind,! S.H.,! Traboulsee,! A.L.,! Moore,! G.R.,! Li,! D.K.,! Mackay,! A.L.! 2007a.! Long! T2! water! in! multiple! sclerosis:! what! else! can! we! learn! from! multi%echo! T2! relaxation?! J! Neurol! 254(11),!1579%87.!doi:10.1007/s00415%007%0595%7.!
Laule,!C.,!Vavasour,!I.M.,!Madler,!B.,!Kolind,!S.H.,!Sirrs,!S.M.,!Brief,!E.E.,!Traboulsee,!A.L.,!Moore,!G.R.,!Li,!D.K.,! MacKay,! A.L.! 2007b.! MR! evidence! of! long! T2! water! in! pathological! white! matter.! J! Magn! Reson! Imaging!26(4),!1117%21.!doi:10.1002/jmri.21132.!
Lebel,!C.,!Gee,!M.,!Camicioli,!R.,!Wieler,!M.,!Martin,!W.,!Beaulieu,!C.!2012.!Diffusion!tensor!imaging!of!white! matter! tract! evolution! over! the! lifespan.! Neuroimage! 60(1),! 340%52.! doi:10.1016/j.neuroimage.2011.11.094.!
Leemans,!A.!2009.!ExploreDTI:!a!graphical!toolbox!for!processing,!analyzing,!and!visualizing!diffusion!MR! data.!17th!Annual!Meeting!of!Intl!Soc!Mag!Reson!Med,!Hawaii,!USA,!pp!p.!3537.!
Leemans,! A.,! Jones,! D.K.! 2009.! The! B%Matrix! Must! Be! Rotated! When! Correcting! for! Subject! Motion! in! DTI! Data.!Magnet!Reson!Med!61(6),!1336%49.!doi:Doi!10.1002/Mrm.21890.!
Madden,! D.J.,! Whiting,! W.L.,! Huettel,! S.A.,! White,! L.E.,! MacFall,! J.R.,! Provenzale,! J.M.! 2004.! Diffusion! tensor! imaging!of!adult!age!differences!in!cerebral!white!matter:!relation!to!response!time.!Neuroimage! 21(3),!1174%81.!doi:10.1016/j.neuroimage.2003.11.004.!
Madler,!B.,!Drabycz,!S.A.,!Kolind,!S.H.,!Whittall,!K.P.,!MacKay,!A.L.!2008.!Is!diffusion!anisotropy!an!accurate! monitor! of! myelination?! Correlation! of! multicomponent! T2! relaxation! and! diffusion! tensor! anisotropy!in!human!brain.!Magn!Reson!Imaging!26(7),!874%88.!doi:10.1016/j.mri.2008.01.047.! Maedler,! B.,! MacKay,! A.! 2007.! Towards! whole! brain! myelin! imaging.! International! Society! for! Magnetic!
Resonance!in!Medicine,!Berlin,!Germany,!pp!1723.!
Melbourne,! A.,! Eaton%Rosen,! Z.,! Bainbridge,! A.,! Kendall,! G.S.,! Cardoso,! M.J.,! Robertson,! N.J.,! Marlow,! N.,! Ourselin,! S.! 2013.! Measurement! of! myelin! in! the! preterm! brain:! multi%compartment! diffusion!
imaging! and! multi%component! T2! relaxometry.! Medical! image! computing! and! computer%assisted! intervention! :! MICCAI! ! International! Conference! on! Medical! Image! Computing! and! Computer% Assisted!Intervention!16(Pt!2),!336%44.!
Mori,!S.,!Wakana,!S.,!Nagae%Poetscher,!L.M.,!P.C.M.,!v.Z.!2005.!MRI!Atlas!of!Human!White!Matter.!Elsevier.! Pannese,!E.!2011.!Morphological!changes!in!nerve!cells!during!normal!aging.!Brain!Struct!Funct!216(2),!85%
9.!doi:10.1007/s00429%011%0308%y.!
Pfefferbaum,! A.,! Sullivan,! E.V.,! Hedehus,! M.,! Lim,! K.O.,! Adalsteinsson,! E.,! Moseley,! M.! 2000.! Age%related! decline!in!brain!white!matter!anisotropy!measured!with!spatially!corrected!echo%planar!diffusion! tensor! imaging.! Magnetic! resonance! in! medicine! :! official! journal! of! the! Society! of! Magnetic! Resonance!in!Medicine!/!Society!of!Magnetic!Resonance!in!Medicine!44(2),!259%68.!
Poot,! D.H.,! den! Dekker,! A.J.,! Achten,! E.,! Verhoye,! M.,! Sijbers,! J.! 2010.! Optimal! experimental! design! for! diffusion! kurtosis! imaging.! IEEE! Trans! Med! Imaging! 29(3),! 819%29.! doi:10.1109/TMI.2009.2037915.!
Prasloski,!T.,!Madler,!B.,!Xiang,!Q.S.,!Mackay,!A.,!Jones,!C.!2011.!Applications!of!stimulated!echo!correction!to! multicomponent!T(2)!analysis.!Magnetic!resonance!in!medicine!:!official!journal!of!the!Society!of! Magnetic! Resonance! in! Medicine! /! Society! of! Magnetic! Resonance! in! Medicine.! doi:10.1002/mrm.23157.!
Prasloski,!T.,!Rauscher,!A.,!MacKay,!A.L.,!Hodgson,!M.,!Vavasour,!I.M.,!Laule,!C.,!Madler,!B.!2012.!Rapid!whole! cerebrum! myelin! water! imaging! using! a! 3D! GRASE! sequence.! Neuroimage! 63(1),! 533%9.! doi:10.1016/j.neuroimage.2012.06.064.! Raz,!N.,!Gunning,!F.M.,!Head,!D.,!Dupuis,!J.H.,!McQuain,!J.,!Briggs,!S.D.,!Loken,!W.J.,!Thornton,!A.E.,!Acker,!J.D.! 1997.!Selective!aging!of!the!human!cerebral!cortex!observed!in!vivo:!differential!vulnerability!of! the!prefrontal!gray!matter.!Cereb!Cortex!7(3),!268%82.! Salat,!D.H.,!Lee,!S.Y.,!van!der!Kouwe,!A.J.,!Greve,!D.N.,!Fischl,!B.,!Rosas,!H.D.!2009.!Age%associated!alterations! in!cortical!gray!and!white!matter!signal!intensity!and!gray!to!white!matter!contrast.!Neuroimage! 48(1),!21%8.!doi:10.1016/j.neuroimage.2009.06.074.!
Salat,! D.H.,! Tuch,! D.S.,! Greve,! D.N.,! van! der! Kouwe,! A.J.,! Hevelone,! N.D.,! Zaleta,! A.K.,! Rosen,! B.R.,! Fischl,! B.,! Corkin,! S.,! Rosas,! H.D.,! Dale,! A.M.! 2005.! Age%related! alterations! in! white! matter! microstructure! measured! by! diffusion! tensor! imaging.! Neurobiol! Aging! 26(8),! 1215%27.! doi:10.1016/j.neurobiolaging.2004.09.017.!
Song,!S.K.,!Yoshino,!J.,!Le,!T.Q.,!Lin,!S.J.,!Sun,!S.W.,!Cross,!A.H.,!Armstrong,!R.C.!2005.!Demyelination!increases! radial! diffusivity! in! corpus! callosum! of! mouse! brain.! Neuroimage! 26(1),! 132%40.! doi:Doi! 10.1016/J.Neuroimage.2005.01.028.!
Stanisz,!G.J.,!Webb,!S.,!Munro,!C.A.,!Pun,!T.,!Midha,!R.!2004.!MR!properties!of!excised!neural!tissue!following! experimentally! induced! inflammation.! Magnetic! resonance! in! medicine! :! official! journal! of! the! Society! of! Magnetic! Resonance! in! Medicine! /! Society! of! Magnetic! Resonance! in! Medicine! 51(3),! 473%9.!doi:10.1002/mrm.20008.!
Sullivan,!E.V.,!Pfefferbaum,!A.!2006.!Diffusion!tensor!imaging!and!aging.!Neurosci!Biobehav!R!30(6),!749%61.! doi:10.1016/j.neubiorev.2006.06.002.!
Tournier,! J.D.,! Mori,! S.,! Leemans,! A.! 2011.! Diffusion! tensor! imaging! and! beyond.! Magn! Reson! Med! 65(6),! 1532%56.!doi:10.1002/mrm.22924.!
Van! Hecke,! W.,! Leemans,! A.,! D'Agostino,! E.,! De! Backer,! S.,! Vandervliet,! E.,! Parizel,! P.M.,! Sijbers,! J.! 2007.! Nonrigid! coregistration! of! diffusion! tensor! images! using! a! viscous! fluid! model! and! mutual! information.!IEEE!Trans!Med!Imaging!26(11),!1598%612.!doi:Doi!10.1109/Tmi.2007.906786.! Van!Hecke,!W.,!Leemans,!A.,!Sage,!C.A.,!Emsell,!L.,!Veraart,!J.,!Sijbers,!J.,!Sunaert,!S.,!Parizel,!P.M.!2011.!The!
effect! of! template! selection! on! diffusion! tensor! voxel%based! analysis! results.! Neuroimage! 55(2),! 566%73.!doi:10.1016/j.neuroimage.2010.12.005.!
Vavasour,!I.M.,!Laule,!C.,!Li,!D.K.,!Traboulsee,!A.L.,!MacKay,!A.L.!2011.!Is!the!magnetization!transfer!ratio!a! marker! for! myelin! in! multiple! sclerosis?! J! Magn! Reson! Imaging! 33(3),! 713%8.! doi:10.1002/jmri.22441.! Vos,!S.B.,!Jones,!D.K.,!Viergever,!M.A.,!Leemans,!A.!2011.!Partial!volume!effect!as!a!hidden!covariate!in!DTI! analyses.!Neuroimage!55(4),!1566%76.!doi:Doi!10.1016/J.Neuroimage.2011.01.048.! Wheeler%Kingshott,!C.A.,!Cercignani,!M.!2009.!About!"axial"!and!"radial"!diffusivities.!Magnetic!resonance!in! medicine!:!official!journal!of!the!Society!of!Magnetic!Resonance!in!Medicine!/!Society!of!Magnetic! Resonance!in!Medicine!61(5),!1255%60.!doi:10.1002/mrm.21965.!
Whitaker,! K.J.,! Kolind,! S.H.,! MacKay,! A.L.,! Clark,! C.M.! 2008.! Quantifying! development:! Investigating! highly! myelinated! voxels! in! preadolescent! corpus! callosum.! Neuroimage! 43(4),! 731%5.! doi:10.1016/j.neuroimage.2008.07.038.!
Whittall,!K.P.,!Mackay,!A.L.!1989.!Quantitative!Interpretation!of!Nmr!Relaxation!Data.!J!Magn!Reson!84(1),! 134%52.!doi:Doi!10.1016/0022%2364(89)90011%5.!
Winston,! G.P.,! Micallef,! C.,! Symms,! M.R.,! Alexander,! D.C.,! Duncan,! J.S.,! Zhang,! H.! 2014.! Advanced! diffusion! imaging!sequences!could!aid!assessing!patients!with!focal!cortical!dysplasia!and!epilepsy.!Epilepsy! Res!108(2),!336%9.!doi:10.1016/j.eplepsyres.2013.11.004.!
Zhang,! H.,! Schneider,! T.,! Wheeler%Kingshott,! C.A.,! Alexander,! D.C.! 2012.! NODDI:! practical! in! vivo! neurite! orientation! dispersion! and! density! imaging! of! the! human! brain.! Neuroimage! 61(4),! 1000%16.! doi:10.1016/j.neuroimage.2012.03.072.!
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
T1 brain average DWI (b=1000) Diffusion tensor (b=2800) Population-based template in register with MNI space First echo• Male: N = 15, age (mean/S.D./min./max.) = 41.2/14.0/19.3/64.3 • Female: N = 15, age (mean/S.D./min./max.) = 40.8/14.5/19.4/64.3
…
Individual WM mask (c2 > 0.8) (incl.)
Yellow: mean c2 > 0.8 (incl.); Blue: ventricle (excl.); Red: basal ganglia and thalamus (excl.)
…
VBA analysis
ROI analysis
T1 space
dMRI space MET2 space
Affine MI Diff. MI Diff. CC e dMRI Aff. NR Tensor- based Creation of population-based template
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
Cerebral WMMA
N
U
SC
R
IP
T
AC
C
EP
TE
D
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
Cerebral WMMA
N
U
SC
R
IP
T
AC
C
EP
TE
D
MA
N
U
SC
R
IP
T
AC
C
EP
TE
D
RD (mm 2/s x 10 -4)Sagittal stratum (includes ILF and IFOF) Anterior limbs of internal capsule
